Does COVID-19 antibody serology testing correlate with disease severity? An analytical descriptive retrospective study

Abstract

Aim: To find out if there is any correlation between COVID-19 antibody serological testing and symptom severity. Methods: This study is a case series of 44 consecutive patients confirmed with COVID-19 who are divided into a group of 23 patients with mild disease and a group of 21 patients with severe disease. All 44 samples were confirmed positive SARS-CoV-2. Subsequent recombinant SARS-CoV-2 S1/S2 IgG test was performed for all patients and all patients developed neutralizing antibodies with altered range. Main outcomes: IgG level and its correlation with disease severity, demographic data, underlying comorbidities, clinical presentation, and treatment comparison between mild and severe disease groups. Results: Quantitative SARS COV-2 IgG was significantly higher in moderate and severe disease groups compared with those in the mild disease group. COVID-19 infection was more prevalent in male, Saudi nationals and smokers with comorbidities and higher inflammatory markers are more in the severe group than in the mild group which necessitates more management options to be taken for severe group patients. Conclusion: IgG antibody level was higher in the severe disease group. Also, the study showed significant differences between the mild and severe disease groups in terms of demographic, clinical, and management variables.

Comparative study of six SARS-CoV-2 serology assays: Diagnostic performance and antibody dynamics in a cohort of hospitalized patients for moderate to critical COVID-19

“…Furthermore, Oved et al 14 noted that SARS-CoV-2 Ab titers were significantly correlated to disease severity with a significant trend from asymptomatic to mild to moderate/severe patients. Two other studies 23,24 reported significantly higher titers in patients with moderate/severe COVID-19 comparatively to those with mild disease. This increased humoral response could be due to higher viral loads in severe COVID-19 patients.…”

Refining COVID-19 retrospective diagnosis with continuous serological tests: a Bayesian mixture model

“…A spectrum bias occurs when the sample of known infected is not representative of infected individuals in the population under study. This bias is often suspected, as symptomatic individuals are more likely to be detected and therefore recruited to study sensitivity, and are also more likely to have higher antibody levels [13][14][15][16]. In that case, a sensitivity parameter can be estimated in each infected sub-group (symptomatic or asymptomatic).…”